 A score-based threshold effect test in time series modelsShufang Wei, Yaping Deng and Yaxing Yang Computational Statistics & Data Analysis, 2025, vol. 212, issue C Abstract: A score-based test statistic is developed to compare a linear ARMA model with its threshold extension. In particular, the focus is on testing the threshold effect in continuous threshold models with no jump at the threshold. Notably, while developed for continuous threshold models, the proposed test remains effective for discontinuous cases. The proposed test does not require fitting the model under the alternative hypothesis, making it computationally more efficient than the quasi-likelihood ratio test. The asymptotic distributions of the score-based test statistic are derived under both the null hypothesis and local alternatives. Simulations indicate that the proposed test has better size than the quasi-likelihood ratio test and demonstrates stronger power compared to the Lagrange Multiplier test. The asymptotic theory of the least square estimation for the continuous threshold ARMA model is further established. An application to the quarterly U.S. civilian unemployment rates data is given. Keywords: Time series models; Threshold effect; Score-based test; Asymptotic theory (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:212:y:2025:i:c:s0167947325001124 DOI: 10.1016/j.csda.2025.108236 Access Statistics for this article Computational Statistics & Data Analysis is currently edited by S.P. Azen More articles in Computational Statistics & Data Analysis from Elsevier |
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